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252
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ICIP
2001
IEEE
16 years 8 months ago
EM algorithms of Gaussian mixture model and hidden Markov model
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
Guorong Xuan, Wei Zhang, Peiqi Chai
CIKM
2004
Springer
15 years 12 months ago
Unified filtering by combining collaborative filtering and content-based filtering via mixture model and exponential model
Collaborative filtering and content-based filtering are two types of information filtering techniques. Combining these two techniques can improve the recommendation effectiveness....
Luo Si, Rong Jin
GECCO
2007
Springer
201views Optimization» more  GECCO 2007»
16 years 19 days ago
A parallel framework for loopy belief propagation
There are many innovative proposals introduced in the literature under the evolutionary computation field, from which estimation of distribution algorithms (EDAs) is one of them....
Alexander Mendiburu, Roberto Santana, Jose Antonio...
CVPR
2007
IEEE
16 years 8 months ago
Learning Conditional Random Fields for Stereo
State-of-the-art stereo vision algorithms utilize color changes as important cues for object boundaries. Most methods impose heuristic restrictions or priors on disparities, for e...
Daniel Scharstein, Chris Pal
174
Voted
RECOMB
2006
Springer
16 years 6 months ago
Detecting the Dependent Evolution of Biosequences
Abstract. A probabilistic graphical model is developed in order to detect the dependent evolution between different sites in biological sequences. Given a multiple sequence alignme...
Jeremy Darot, Chen-Hsiang Yeang, David Haussler